CN114449609B - LEACH clustering routing method based on energy consumption balance - Google Patents

LEACH clustering routing method based on energy consumption balance Download PDF

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CN114449609B
CN114449609B CN202210162981.4A CN202210162981A CN114449609B CN 114449609 B CN114449609 B CN 114449609B CN 202210162981 A CN202210162981 A CN 202210162981A CN 114449609 B CN114449609 B CN 114449609B
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焦俊
查文文
朱诚
彭硕
辜丽川
时国龙
马慧敏
陶亮
刘东阳
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Anhui Agricultural University AHAU
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

In the cluster head election stage, the nodes with large residual energy and more neighbor nodes and close to the BS are selected as cluster heads; then, the non-cluster head node calculates the cost of adding different clusters according to the strength and the residual energy of communication signals between the non-cluster head node and different cluster heads, and adds the cluster with the minimum cost; in the data transmission stage, if the information sending cluster head is beyond one-hop distance from the base station, the cluster head needs to consider the factors of residual energy of each neighbor cluster head, the number of nodes in the cluster, the distance between the cluster head and the BS and the like, calculate the forwarding probability of each neighbor cluster head, and select the neighbor cluster head with the maximum forwarding probability value as the next-hop relay node. Compared with LEACH, LEACH-C and FIGPO, the invention can prolong the life cycle of the network and simultaneously enable the BS to receive more data.

Description

LEACH clustering routing method based on energy consumption balance
Technical Field
The invention relates to the field of radar control, in particular to an LEACH clustering routing method based on energy consumption balance.
Background
Energy efficiency is a main problem faced by the development of the wireless sensor network WSN, and a clustering-based routing protocol is one of effective methods for solving the problem. The classic Clustering protocol LEACH (Low Energy Adaptive Clustering Hierarchy, LEACH) selects a cluster head according to a preset probability, energy consumption of the WSN is balanced by periodically rotating the cluster head, the selected cluster head cannot be guaranteed to be sufficient in Energy and reasonable in position, and meanwhile, the cluster head sends data to a Base Station (BS) in a single-hop mode, so that Energy consumption of the cluster head is increased, and the life cycle of the WSN is shortened.
Disclosure of Invention
The present invention is to overcome the problems in the prior art, and provide an LEACH clustering routing method based on energy consumption balancing to solve the problems in the background art.
Therefore, the invention provides an LEACH clustering routing method based on energy consumption balance, which comprises the following steps:
a first election stage
Calculating to obtain a threshold value of each node becoming a cluster head according to a distance factor between each node and the BS, a residual energy factor of the node and a neighbor number factor of the node;
determining whether each node is a cluster head according to the threshold value T (n) of each node;
two clustering stages
The node which becomes the cluster head broadcasts information which becomes the cluster head of the node, wherein the information comprises the ID and the residual energy of the node;
other non-cluster head nodes calculate the cost of adding into different clusters according to the received information and the distance between the non-cluster head nodes and the cluster heads;
adding the least costly cluster;
three data transmission phases
Constructing a communication path with multiple relay nodes from the information-sending cluster head to the BS;
and calculating the forwarding probability of each neighbor cluster head, selecting the neighbor cluster head with the maximum forwarding probability value as a next hop relay node, and determining the next hop by the selected neighbor cluster head in the same way until the information can be successfully forwarded to the BS.
Further, in the cluster head election phase, according to the distance factor d between the node and the BS i Residual energy factor E i Section (B)Number of point neighbors factor N i Calculating the probability p (i) and the threshold T (n) of each node becoming a cluster head in each round;
E i ＝E(i)/E mean
N i ＝1-|N(i)|/(np)
d i (BSmax-d BS (i))/BSmax
Figure GDA0003518547160000021
Figure GDA0003518547160000031
wherein E (i) and E mean Respectively the residual energy of the node i and the average energy of the active nodes in the WSN; l N (i) l is the number of the active neighbors of the node i in the communication area; n (i) is a neighbor set of the node i; p (i) is the probability of the node i becoming the cluster head; n and np are the total number of network nodes and the number of members in the standard cluster respectively; BSmax is the furthest distance of the WSN internal node to the BS; d is a radical of BS (i) Is the distance between node i and BS; α and β are weighting factors, and are α + β =1;
and determining whether each node is a cluster head according to the threshold value T (n) of each node.
Further, in the clustering stage, when the non-cluster-head node i calculates the cost for itself to join the cluster, if there are a plurality of cluster heads h in the communication area of the node i and the communication cost is related to the distance factor, the cost formula for i to join the closest cluster is:
costF(i，h)∝dis(i，h)
the non-cluster head node should join the cluster with least members in the cluster, have
costF(i，h)∝|N(h)|
When the WSN is operated, the non-cluster-head node should select the cluster with the cluster head with more residual energy to join, including
Figure GDA0003518547160000032
Push to get cost function
Figure GDA0003518547160000033
Wherein E is 0 Initial energy for all nodes; l N (h) l is the number of neighbor nodes of the cluster head h; dis (i, h) is the distance between the node i and the cluster head h; a1, a2, a3 are weighting factors, and a 1 +a 2 +a 3 ＝1。
Further, in the data transmission phase, by
Figure GDA0003518547160000041
Calculating the forwarding probability;
wherein the content of the first and second substances,
Figure GDA0003518547160000042
wherein, tau ih Is the distance between nodes i and h.
The LEACH clustering routing method based on energy consumption balance has the following beneficial effects:
in the cluster head election stage, the residual energy, the node density, the distance factor between the candidate cluster head node and the BS and the like of the candidate cluster head node are comprehensively considered, the election threshold value is optimized, and the generated cluster head is reasonable; in the clustering stage, the non-cluster-head node calculates the cost between the non-cluster-head node and the cluster head, and adds the cluster with the minimum cost; inter-cluster communication is that on the basis of comprehensively considering factors such as cluster head residual energy, the number of members in a cluster, the distance between a relay cluster head and a Base Station (BS), and the like, multi-hop communication is formed between the cluster head and the base station, and the energy consumption of network nodes is balanced;
compared with LEACH, LEACH-C and FIGWO, the invention can respectively prolong the life cycle of the network by 60%, 43.1% and 13.36%, and compared with the network adopting other three protocols, the BS can receive more data.
Drawings
FIG. 1 is a schematic diagram of the basic model of NS 3;
FIG. 2 is a network node distribution diagram;
FIG. 3 is a network lifecycle for different protocol conditions;
FIG. 4 is a graph of node death times for different protocol conditions;
FIG. 5 illustrates network residual energy under different protocol conditions;
FIG. 6 is a comparison of BS received packets;
FIG. 7 is a total packet received by the BS;
FIG. 8 is a comparison of network life cycle under BS dynamic conditions;
fig. 9 shows the network residual energy under BS dynamic conditions.
Detailed Description
One embodiment of the present invention will be described in detail below with reference to the accompanying drawings, but it should be understood that the scope of the invention is not limited to the embodiment.
In the present application, the type and structure of components that are not specified are all the prior art that is well known to those skilled in the art, and those skilled in the art can set the components according to the needs of the actual situation, and the embodiments in the present application are not specifically limited.
Specifically, the embodiment of the invention provides an LEACH clustering routing method based on energy consumption balance, which comprises a cluster establishment stage and a data stable transmission stage, wherein the cluster establishment stage comprises two steps of selecting a cluster head and entering a node into a cluster; in the stable data transmission stage, the cluster head collects member information in the cluster and transmits the information to the BS in a single-hop or multi-hop mode.
One choice cluster head (cluster head election phase)
The classic LEACH protocol is to set the proportion p of the cluster head in all nodes in advance, and meanwhile, p is always unchanged in the WSN full life period. p together with the current round number r determines the threshold T (n). Obviously, with the operation of the WSN, the energy consumption of each node is increased, and the number of dead nodes is increased, and if the probability that a node becomes a cluster head is measured by a fixed p, it is unreasonable to ignore the residual energy of the node. In the practical application of the WSN, the position of the node is an influence factor which influences the node to become a cluster head, and if the node is far away from the BS, the node needs to consume more transmission energy and transmits information to a destination; if the source cluster head transmits information in a multi-hop mode, a plurality of relay nodes are needed to forward the information, so that the overall energy consumption of the WSN is increased, and therefore the selected cluster head should be close to the BS; if the number of the selected cluster head neighbors is large, the average distance from the cluster head to the cluster members is shortened when the selected cluster head neighbors provide services for the cluster members, and the energy consumption in the cluster is reduced accordingly.
In summary, the invention comprehensively considers the distance factor d i Residual energy factor E i Node neighbor number factor N i On the basis of the above steps, the probability that each node becomes a cluster head in each round is calculated, a calculation formula influencing the cluster head factor and a threshold value formula T (n) are shown in formulas (5) to (9),
E i ＝E(i)/E mean (5)
N i ＝1-|N(i)|/(np) (6)
d i ＝(BSmax-d BS (i))/BSmax (7)
Figure GDA0003518547160000071
Figure GDA0003518547160000072
in the formula, E (i) and E mean Respectively the residual energy of the node i and the average energy of the active nodes in the WSN; l N (i) l is the number of the active neighbors of the node i in the communication area; n (i) is a neighbor set of the node i; p (i) is the probability that node i becomes the cluster head; n isNp is the total number of network nodes and the number of members in the standard cluster respectively; BSmax is the maximum distance from the WSN internal node to the BS; d BS (i) Is the distance between node i and BS; α and β are weighting factors, and α + β =1.
It can be seen from the derivation analysis of equations (5) to (9) that when the node has larger residual energy, more neighboring nodes and a short distance from BS, the values of p (i) and T (n) are correspondingly larger, and then the node has a high probability of generating a random number between [0-1] and lower than the value of T (n), or the node has a high probability of becoming a cluster head. Therefore, the present invention is reasonable in cluster head selection.
Two nodes clustering (clustering stage)
Once the nodes are determined to be the cluster head, they broadcast a message that they become the cluster head, which contains information such as the ID and remaining energy of the nodes. And other non-cluster head nodes calculate the cost for adding into different clusters by themselves according to the received information and factors such as the distance between the non-cluster head nodes and the cluster head, and add into the cluster with the minimum cost.
The cost between the node i and the cluster head h relates to the residual energy of the cluster head h, the number of neighbors and the distance from the node i. If a plurality of cluster heads exist in the communication area of the node i, if the communication cost only considers the distance factor, the cost calculation formula of the nearest cluster added to the node i is shown as the formula (10).
costF(i，h)∝dis(i，h) (10)
Because the number of neighbor nodes of a cluster head affects the scale and energy consumption of the cluster, a cluster head with more neighbors needs to provide more data forwarding services, so that the energy consumption of the cluster head is accelerated, and the overall performance of the network is reduced. Therefore, the non-cluster head node should join the cluster with fewer members in the cluster, and balance the scale of each cluster, that is:
costF(i，h)∝|N(h)| (11)
when the WSN runs, the energy consumption of the cluster head is higher than that of a common node, and then the node should select the cluster with the cluster head with more residual energy to join [15] Namely:
Figure GDA0003518547160000081
integrating equations (10) - (12), a cost function is derived:
Figure GDA0003518547160000091
in the formula, E 0 Initial energy for all nodes; l N (h) l is the number of neighbor nodes of the cluster head h; dis (i, h) is the distance between the node i and the cluster head h; a1, a2, a3 are weighting factors, and a 1 +a 2 +a 3 =1, these weighting factors can be adjusted to the extent to which the individual factors in the equation (13) influence the cost function.
Communication between three clusters (data transmission phase)
In practical application, if the information sending cluster head is far away from the BS, a communication path with multiple relay nodes needs to be constructed to the BS, and the relay nodes are some cluster heads which are close to the BS. When the information sending cluster head selects the next hop relay node, the distance between the information sending cluster head and the relay node needs to be considered.
Before the information is sent to the cluster head to select the relay node, the information of the neighbor cluster head needs to be collected, and the cluster head broadcasts the information of the cluster head in the communication area of the cluster head and receives the information broadcasted by the neighbor cluster head, wherein the information comprises the ID of the cluster head, the distance between the cluster head and the BS, the residual energy and the like. After the broadcast is finished, each cluster head can know the information of all the neighbor cluster heads. The information sending cluster head calculates the forwarding probability of each neighbor cluster head by combining the formula (14) on the basis of considering factors such as the residual energy of the neighbor cluster head, the number of nodes in the cluster, the distance between the neighbor cluster head and the BS and the like, the neighbor cluster head with the maximum forwarding probability value is selected as a next hop relay node, and the selected neighbor cluster head determines the next hop in the same way until the information can be successfully forwarded to the BS.
Assuming that the information sending cluster head i and the neighbor cluster head node h, the probability calculation formula of i forwarding information to the BS through h is as shown in the formula (14).
Figure GDA0003518547160000101
In the formula (I), the compound is shown in the specification,
Figure GDA0003518547160000102
in the formula, τ ih Is the distance between nodes i and h. As can be seen from equations (14) and (15), if the neighbor cluster head h has a small number of neighbors, high residual energy, and close distances to both the cluster head i and the BS, the probability that the cluster head h is selected as the relay point is higher.
Simulation test section
In order to test and evaluate the performance of the invention, a discrete event network simulator NS3 is adopted to build a simulation platform. The simulation hardware processor is Inter Core i7, the memory is XGB, the version number of the virtual machine is VMware Workstation10.0.4, and the version number of Ubuntu is 16.4LTS.
1 architecture of simulation System
The NS3 is mainly used for constructing a simulation network having multiple simulation nodes, and the simulation model structure is as shown in fig. 2, and each node has a transmission/reception function. As shown in fig. 2, in the data packet transmission process, the NS3 has a clear hierarchy, the upper layer sending function of the source node calls the lower layer sending function to transmit the data packet, and the lower layer receiving function of the destination node calls the upper layer receiving function to deliver the data packet to the peer layer.
The simulation operation of the network is data transmission at each layer, and the NS3 network simulation architecture, as shown in fig. 1, is composed of a plurality of network components, including nodes, applications, protocol stacks, network devices, channels, and the like.
The Node in fig. 1 is similar to a computer to which various functions can be added, and is described by a Node class in C + +, and is various methods for managing network component representation in a simulator, including application programs, protocol stacks, and the like; the Application is a user program for generating some simulation activities and is also described by Application classes in C + +; a Channel is an object connecting a node to a data exchange Channel and is a medium through which data streams flow in a network; netDevice is equivalent to a network device installed on a node, and includes hardware devices and software drivers that enable the node to communicate with other nodes over a channel.
2 simulation analysis
After the simulation environment is built, four protocols of LEACH, LEACH-C, FIGWOO and the method are analyzed and compared. Assuming that 100 nodes are randomly distributed in a 100 x 100m2 area, all nodes have the same initial energy, the simulation parameters are shown in table 1. The BS is located outside the center of the network environment, and the network node distribution is shown in fig. 2.
TABLE 1 simulation parameter settings for networks and energy consumption models
Figure GDA0003518547160000111
Figure GDA0003518547160000121
(1) WSN lifecycle analysis
Figure 3 depicts the number of dead nodes of a WSN as a function of time using the four network protocols LEACH, LEACH-C, figs, and the present invention, respectively. Supposing that the death round number of the first node of the WSN is defined as the life cycle of the WSN, as can be seen from FIG. 3, no matter what protocol is adopted, the WSN is in an unstable state after the first node is dead, and it can be found from the graph that the number of dead nodes is increased along with the prolonging of the operation time of the WSN, but the life cycle of the network adopting the invention is longest and the death rate of the nodes is lowest, because the protocol of the invention determines the cluster head after comprehensively considering the factors of the residual energy of the nodes, the number of neighbor nodes, the distance from the node to the BS and the like, and when the non-cluster head node is clustered, the cost is considered, so that the distribution of the cluster is more scientific and reasonable. In addition, the cluster head node communicates with the BS in a multi-hop mode, so that the energy consumption of the cluster head is reduced, and the WAN survival period is prolonged.
Fig. 4 shows the time comparison of the death of the first node, 10% of the death of the first node and the total death of the nodes of the network when the WSN adopts the four protocols respectively, and it is found from the figure that the death times of the first node adopting the four protocols respectively are 875 rounds, 978 rounds, 1235 rounds and 1400 rounds; the 10% node death times were 966, 1070, 1354 and 1539 rounds, respectively; the death times of all nodes were 1269, 1301, 1639 and 2496 rounds, respectively. Compared with LEACH, LEACH-C and FIGWO, the life cycle of the invention is respectively improved by 60%, 43.1% and 13.36%, therefore, the protocol of the invention effectively prolongs the life cycle of the network.
(2) WSN energy consumption performance analysis jj640123
With the operation of the WSN, no matter which protocol is adopted, the network residual energy shows a descending trend, and as can be seen from FIG. 5, the decline of the curve of the network residual energy adopting the method is gentle, and the network energy consumption is obviously lower than that of the network adopting other three protocols. At 1500 rounds, the network energy adopting LEACH, LEACH-C and FIGWO protocols is completely exhausted, and at the moment, the residual energy is 12J by adopting the method, and the residual energy is exhausted at 2350 rounds. Therefore, compared with other 3 protocols, the protocol has higher efficient energy utilization rate and energy-saving effect, because the energy consumption of each cluster head node is balanced by comprehensively considering the number of cluster head neighbor nodes, the distance from the cluster head neighbor nodes to a BS (base station), the node residual energy and other influence factors when the cluster head elects, the nodes enter the cluster and the inter-cluster communication, the WSN has more surviving nodes and more residual energy in the same running time under the same network environment.
(3) BS received packet analysis
When the WSN operates using these four protocols, respectively, the time-varying profile of the packets received by the BS is shown in fig. 6, from which it can be seen that when the WSN uses the protocol of the present invention, the number of packets received by the BS is always greater than the number of packets received using the other 3 protocols. When the WSN respectively adopts LEACH and LEACH-C protocols, the number of data packets received by the BS is not increased after 1300 rounds of operation, and when the FIGWO protocol is adopted, the BS reaches saturation after 1500 rounds of data packets are received. When the WSN uses the protocol of the present invention, the data packets received by the BS are increased until after 2000 rounds. Therefore, the data transmission capability is obviously better by adopting the invention.
Fig. 7 shows the total amount of packets received by the BS at the end of its lifecycle for a WSN using 4 protocols, respectively. It can be seen from the figure that when the network adopts the protocol of the present invention, the number of the data packets received by the BS is 26.22 times, 10.71 times and 2.88 times of those of the protocols of LEACH, LEACH-C and FIGWO, respectively, because the WSN adopts the protocol of the present invention, the energy consumption of the node is reduced, especially there are still many live cluster heads in the later stage of WSN operation, and the node data in the fusion cluster is transmitted to the BS, thereby prolonging the life cycle.
(4) WSN life cycle and energy consumption analysis under BS mobile state condition
During the application process of the WSN, the topological structure of the WSN is changed due to the movement of the BS. If the WSN and experimental parameter configuration are as in table 1, fig. 8 and 9 show the results of the simulation of the network life cycle and remaining energy as the BS moves from coordinates (50, 0) to (50, 130) when the WSN employs four different protocols, respectively. It can be seen from fig. 8 that the node using the protocol of the present invention dies first in 830 rounds, and the first node using the LEACH, LEACH-C, and FIGWO protocol clusters dies in 870 rounds, 975 rounds, and 1121 rounds, but the reason for this is that the distance between the candidate node and the BS is considered when selecting the cluster head, so that the node close to the BS has more chances to become the cluster head in each round of cluster head selection, and meanwhile, part of the cluster heads near the BS are frequently used as relay nodes, and die too much energy and prematurely, but in general, the survival time of using the present invention is longest, and the node death rate is lower than that of using other 3 protocols, because the protocol of the present invention ensures the rationality of cluster head selection, reduces the communication energy consumption between nodes, and increases the survival time of the node.
Although the dead node appears in the first time in the invention, the remaining total energy is always higher than that of the network adopting other 3 protocols in the whole network running time, and the comparison is shown in fig. 9, which shows that the protocol of the invention designed herein can prolong the service life of the network and save the energy of the network when the distance, the energy, the neighbor nodes and other factors are comprehensively considered to form a cluster.
In summary, the invention provides a clustering routing protocol for solving the problems of unbalanced energy consumption, short network lifetime and the like of a WSN-free network, and the protocol takes the residual energy of nodes and the distance from the nodes to a BS into consideration when selecting a cluster head; when clustering, considering the cluster scale, energy and the distance between a cluster head and a BS; and finally, when the communication distance between the cluster head and the BS is greater than one hop, introducing a relay node acted by the cluster head, and forwarding the auxiliary data to the BS. Simulation experiment results show that: compared with LEACH, LEACH-C and FIGWO protocols, the invention has the advantages of clustering energy balance, prolonging the life cycle and sending more data packets to the BS.
The above disclosure is only for a few specific embodiments of the present invention, however, the present invention is not limited to the above embodiments, and any modifications that can be made by those skilled in the art are intended to fall within the scope of the present invention.

Claims (1)

1. A classic clustering protocol LEACH clustering routing method based on energy consumption balance is characterized by comprising the following steps:
election stage of cluster head
Calculating to obtain a threshold value of each node becoming a cluster head according to a distance factor between each node and a Base Station (BS), a residual energy factor of the node and a neighbor quantity factor of the node;
determining whether the node is a cluster head according to the threshold T (n) of each node;
stage of clustering
The node which becomes the cluster head broadcasts information which becomes the cluster head of the node, wherein the information comprises the ID and the residual energy of the node;
other non-cluster head nodes calculate the cost of adding into different clusters according to the received information and the distance between the non-cluster head nodes and the cluster heads;
adding the least costly clusters;
data transmission phase
Constructing a communication path with multiple relay nodes from the information-sending cluster head to the BS;
calculating the forwarding probability of each neighbor cluster head, selecting the neighbor cluster head with the maximum forwarding probability value as a next hop relay node, and determining the next hop by the selected neighbor cluster head in the same way until the information can be successfully forwarded to the BS;
in the head election phaseAccording to the node-to-BS distance factor d i Residual energy factor E i Node neighbor number factor N i Calculating the probability p (i) and the threshold T (n) of each node becoming a cluster head in each round;
E i ＝E(i)/E mean
N i ＝1-|N(i)|/(np)
d i ＝(BS max-d BS (i))/BS max
Figure FDA0003906590150000021
Figure FDA0003906590150000022
wherein E (i) and E mean Respectively the residual energy of the node i and the average energy of the active nodes in the WSN; l N (i) | is the number of the living neighbors of the node i in the communication area; n (i) is a neighbor set of the node i; p (i) is the probability of the node i becoming the cluster head; n and np are the total number of network nodes and the number of members in the standard cluster respectively; BSmax is the farthest distance from the internal node of the WSN to the BS; d is a radical of BS (i) Is the distance between node i and BS; α and β are weighting factors, and are α + β =1;
determining whether the node is a cluster head according to the threshold T (n) of each node;
in the clustering stage, when a non-cluster-head node i calculates the cost for adding into a cluster, if a plurality of cluster heads h exist in a communication area of the node i and the communication cost is related to a distance factor, the cost formula for adding into the nearest cluster by the node i is as follows:
costF(i，h)∞dis(i，h)
the non-cluster head node should join the cluster with least members in the cluster, including
costF(i，h)∞|N(h)|
When the WSN is operated, the non-cluster-head node should select the cluster with the cluster head with more residual energy to join, including
Figure FDA0003906590150000031
Push to get cost function
Figure FDA0003906590150000032
Wherein E is 0 Initial energy for all nodes; l N (h) l is the number of neighbor nodes of the cluster head h; dis (i, h) is the distance between the node i and the cluster head h; a1, a2, a3 are weighting factors, and a 1 +a 2 +a 3 ＝1；
In the data transmission phase, by
Figure FDA0003906590150000033
Calculating the forwarding probability;
wherein the content of the first and second substances,
Figure FDA0003906590150000034
wherein, tau ih Is the distance between nodes i and h.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108112048A (en) * 2017-12-28 2018-06-01 重庆邮电大学 Recognize a kind of efficiency route protocol based on stability in sensor network
CN110149672A (en) * 2019-05-24 2019-08-20 贵州大学 A kind of improved I-LEACH routing communication means
CN112312511A (en) * 2020-09-04 2021-02-02 河南大学 Improved LEACH method for balancing energy consumption of wireless sensor network based on tree
CN112367675A (en) * 2020-11-11 2021-02-12 内蒙古大学 Wireless sensor network data fusion method and network system based on self-encoder
CN112822746A (en) * 2021-01-15 2021-05-18 重庆邮电大学 Energy-efficient wireless sensor network clustering algorithm

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100881112B1 (en) * 2007-06-13 2009-02-02 성균관대학교산학협력단 Operating method of wireless sensor networks considering energy efficiency

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108112048A (en) * 2017-12-28 2018-06-01 重庆邮电大学 Recognize a kind of efficiency route protocol based on stability in sensor network
CN110149672A (en) * 2019-05-24 2019-08-20 贵州大学 A kind of improved I-LEACH routing communication means
CN112312511A (en) * 2020-09-04 2021-02-02 河南大学 Improved LEACH method for balancing energy consumption of wireless sensor network based on tree
CN112367675A (en) * 2020-11-11 2021-02-12 内蒙古大学 Wireless sensor network data fusion method and network system based on self-encoder
CN112822746A (en) * 2021-01-15 2021-05-18 重庆邮电大学 Energy-efficient wireless sensor network clustering algorithm

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于贪心算法的通信网络能耗均衡分簇路由优化方法;阮玉生 等;《科学技术创新》;20210405;全文 *

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